LILogicNet trains compact logic-gate networks with learnable sparse connectivity via Top-K selection, reaching 98.45% MNIST accuracy with 8k gates and 60.98% CIFAR-10 accuracy with 256k gates while using far fewer gates than prior logic models.
Gradient-based learning applied to document recog- nition.Proceedings of the IEEE, 86(11):2278–2324, 1998
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LILogic Net: Compact Logic Gate Networks with Learnable Connectivity for Efficient Hardware Deployment
LILogicNet trains compact logic-gate networks with learnable sparse connectivity via Top-K selection, reaching 98.45% MNIST accuracy with 8k gates and 60.98% CIFAR-10 accuracy with 256k gates while using far fewer gates than prior logic models.